Julio C. Urenda

According to our database, Julio C. Urenda authored at least 19 papers between 2008 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Memories of the Future: Systems, Human, and Cybernetic Aspects of the Emerging Post-AI World.

Vladik Kreinovich, Miroslav Svitek, Julio C. Urenda, Olga Kosheleva

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2025

2024

Why 6-Labels Uncertainty Scale in Geosciences: Probability-Based Explanation.

Aaron Velasco, Julio C. Urenda, Olga Kosheleva, Vladik Kreinovich

Proceedings of the New Horizons for Fuzzy Logic, Neural Networks and Metaheuristics, 2024

Fuzzy Techniques Explain the Effectiveness of ReLU Activation Function in Deep Learning.

Julio C. Urenda, Olga Kosheleva, Vladik Kreinovich

Proceedings of the New Horizons for Fuzzy Logic, Neural Networks and Metaheuristics, 2024

2023

Dimension Compactification Naturally Follows from First Principles.

Julio C. Urenda, Olga Kosheleva, Vladik Kreinovich

Proceedings of the Decision Making Under Uncertainty and Constraints - A Why-Book, 2023

Why Menzerath's Law?

Julio C. Urenda, Vladik Kreinovich

Proceedings of the Uncertainty, Constraints, and Decision Making, 2023

Why Homogeneous Membranes Lead to Optimal Water Desalination: A Possible Explanation.

Julio C. Urenda, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich

Proceedings of the Decision Making Under Uncertainty and Constraints - A Why-Book, 2023

Fuzzy Techniques, Laplace Indeterminacy Principle, and Maximum Entropy Approach Explain Lindy Effect and Help Avoid Meaningless Infinities in Physics.

Julio C. Urenda, Sean R. Aguilar, Olga Kosheleva, Vladik Kreinovich

Proceedings of the Decision Making Under Uncertainty and Constraints - A Why-Book, 2023

2022

Why 1/(1+d) Is an Effective Distance-Based Similarity Measure: Two Explanations.

Julio C. Urenda, Olga Kosheleva, Vladik Kreinovich

Proceedings of the IEEE 11th International Conference on Intelligent Systems, 2022

Algebraic Approach to Data Processing - Techniques and Applications

Julio C. Urenda, Vladik Kreinovich

115, Springer, ISBN: 978-3-031-16779-9, 2022

2021

Mexican Folk Arithmetic Algorithm Makes Perfect Sense.

Julio C. Urenda, Christian Servin, Olga Kosheleva, Vladik Kreinovich

Proceedings of the Explainable AI and Other Applications of Fuzzy Techniques, 2021

Why Kappa Regression?

Julio C. Urenda, Orsolya Csiszár, Gábor Csiszár, József Dombi, György Eigner, Olga Kosheleva, Vladik Kreinovich

Proceedings of the Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), 2021

2020

Why Squashing Functions in Multi-Layer Neural Networks.

Julio C. Urenda, Orsolya Csiszár, Gábor Csiszár, József Dombi, Olga Kosheleva, Vladik Kreinovich, György Eigner

Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

How Mathematics and Computing Can Help Fight the Pandemic: Two Pedagogical Examples.

Julio C. Urenda, Olga Kosheleva, Martine Ceberio, Vladik Kreinovich

Proceedings of the Fuzzy Information Processing 2020, 2020

Why a Classification Based on Linear Approximation to Dynamical Systems Often Works Well in Nonlinear Cases.

Julio C. Urenda, Vladik Kreinovich

Proceedings of the Fuzzy Information Processing 2020, 2020

How User Ratings Change with Time: Theoretical Explanation of an Empirical Formula.

Julio C. Urenda, Manuel Hernandez, Natalia Villanueva-Rosales, Vladik Kreinovich

Proceedings of the Fuzzy Information Processing 2020, 2020

Natural Invariance Explains Empirical Success of Specific Membership Functions, Hedge Operations, and Negation Operations.

Julio C. Urenda, Orsolya Csiszár, Gábor Csiszár, József Dombi, György Eigner, Vladik Kreinovich

Proceedings of the Fuzzy Information Processing 2020, 2020

Which Distributions (or Families of Distributions) Best Represent Interval Uncertainty: Case of Permutation-Invariant Criteria.

Michael Beer, Julio C. Urenda, Olga Kosheleva, Vladik Kreinovich

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2020

Why Spiking Neural Networks Are Efficient: A Theorem.

Michael Beer, Julio C. Urenda, Olga Kosheleva, Vladik Kreinovich

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2020

2008

How to reconcile physical theories with the idea of free will: From analysis of a simple model to interval and fuzzy approaches.

Julio C. Urenda, Olga Kosheleva

Proceedings of the FUZZ-IEEE 2008, 2008